In today's Geographic Information Systems (GIS) industry, it is now a common practice to extract Digital Elevation Models (DEMs) from stereo overlapping aerial photography by matching features between two images. Referring to FIG. 1, DEMs are maps representing the elevation of the land surface and normally form a regular grid of equally spaced surface coordinates. Traditionally DEM creation is done using photogrammetric equipment. Today's digital methods use digital image matching techniques (still with 2 or more images) to build the DEM more automatically. The extraction of height information from the images involves the removal of relative (between images) and absolute (using both images) variations of yaw, pitch and roll—also known in the photogrammetric industry as Kappa, Omega and Phi, respectively. In the photogrammetric discipline this process is referred to as relative and absolute orientation. Fully oriented image pairs retain one relative distortion. This distortion is the displacement of features in the direction of motion of the camera due to the differences in height of the objects being imaged. It is referred to as stereoscopic parallax or “X Parallax.”
Once the flying height, the camera principal distance (also referred to as the focal distance) and the Mean Sea Level (MSL) are taken into consideration, the X parallax value reveals feature elevation. While the elevation throughout the stereo model created by the overlap of the two images is continuous, the DEM is normally computed (or sampled) in relation to a discrete grid of points. However, key shape changes of the terrain such as, e.g., break lines at the edges of an alpine road, or sharp drops in the bed of a river down a cascade may be completely missed by the sample points of the DEM. In water runoff studies, for example, such inaccuracies in the DEM information may result in models built from unusable data, rendering the models insignificant for their desired purpose. FIG. 2 illustrates the limited effectiveness of a DEM to represent the terrain.
It is now common for raster imagery to be stored in or referenced from a GIS system. The usual practice is to mosaic the images to a single corrected image, with the photogrammetric distortions removed, and then store them accordingly. The result is referred to as an orthophoto. Orthophotos can also be created directly from stereo pairs of images using the x parallax.
In many computer applications, these images are stored and manipulated in the form of raster image data, or in other words, data derived from breaking the images down into units called pixels, each specified by location and color. The result being that the raster imagery or complete mosaic of images are typically stored as an array of pixels. However, that pixel array is compressed, normalized or facetted, and eventually becomes a serialization of the pixel array. To recover the model of the terrain in three dimensions for analysis, either (a) both stereo images are stored and viewed using some stereo viewing device or (b) one image, mosaic or orthophoto is stored which is then draped over a DEM; approach (b) being the more usual approach as mentioned above. Method (a) requires that both images be stored. This represents twice the storage and since the images are of the same area or objects, is redundant storage in all respects except for the recovery of the 3rd dimension. Approach (b) has all of the challenges and disadvantages noted above. The ideal situation would be that the image need only be stored once as an orthophoto and in a near continuous store of height information (making the recreation possible when both images are stored), with the information being associated with a single image such that no important detail is lost in the reconstructed 3D model and no redundant information needs to be stored.